Scalable Quantum-Classical DFT Embedding for NISQ Molecular Simulation

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Authors: Namrata Manglani, Samrit Kumar Maity, Ranjit Thapa, Sanjay Wandhekar
Cited by: 0

Abstract

Scalable quantum-classical embedding is essential for chemically meaningful simulations on near-term NISQ hardware. Using QDFT, we show systematic recovery of correlation energy relative to the DFT baseline, benchmarked against CCSD in a fixed six-orbital active space across molecules ranging from water to naphthalene. By varying the number of embedded electrons from 2 to 8, aromatic systems saturate near 63-64 percent, while linear molecules such as carbon dioxide reach 68 percent. All systems converge within two embedding iterations under relaxed self-consistency thresholds, highlighting the robustness of the approach. A (4e,6o) active space recovers approximately 60 percent correlation using 10 qubits, providing practical guidelines for NISQ-era simulations.

Fields of Study & Subjects

Quantum Computing Algorithms and Architecture Advanced Chemical Physics Studies Quantum many-body systems

Publication details

Journal / source
IEEE Guwahati Subsection Conference (GCON)
Pages
1–4
Publication date
1 June 2026